XLM-RoBERTa base Universal Dependencies v2.8 POS tagging: Basque

This model is part of our paper called:

  • Make the Best of Cross-lingual Transfer: Evidence from POS Tagging with over 100 Languages

Check the Space for more details.

Usage

from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-eu")
model = AutoModelForTokenClassification.from_pretrained("wietsedv/xlm-roberta-base-ft-udpos28-eu")
Downloads last month
19
Safetensors
Model size
277M params
Tensor type
I64
·
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train wietsedv/xlm-roberta-base-ft-udpos28-eu

Space using wietsedv/xlm-roberta-base-ft-udpos28-eu 1

Evaluation results

  • English Test accuracy on Universal Dependencies v2.8
    self-reported
    65.800
  • Dutch Test accuracy on Universal Dependencies v2.8
    self-reported
    63.500
  • German Test accuracy on Universal Dependencies v2.8
    self-reported
    66.300
  • Italian Test accuracy on Universal Dependencies v2.8
    self-reported
    65.500
  • French Test accuracy on Universal Dependencies v2.8
    self-reported
    61.200
  • Spanish Test accuracy on Universal Dependencies v2.8
    self-reported
    62.000
  • Russian Test accuracy on Universal Dependencies v2.8
    self-reported
    74.900
  • Swedish Test accuracy on Universal Dependencies v2.8
    self-reported
    66.600
  • Norwegian Test accuracy on Universal Dependencies v2.8
    self-reported
    61.800
  • Danish Test accuracy on Universal Dependencies v2.8
    self-reported
    66.500